Last updated: 2021-09-10

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This page…

On this page several ways to explore patterns in Pine stems are presented. Some are interactive; all will take a bit of time to digest and interpret. There are over 5,280 observations from 57 plots that occurred from 1995-2020.

Number of pine stems per plot variable with high of 512 (BP 7_8, 2017)


Stem size per year

Number of stems per size class category. To view limited number of plots select from dropdown.

Stems compared to plots in BU 5

Heatmap Charts

These charts compare number of stems per BU_P to the mean number of stems for BU 5. Notes about the charts:

  • Oranges and Reds = fewer stems than mean of stems for BU 5; Greens = more stems than mean of stems for BU 5
  • Only shows years where there were counts for BU5 and specific BU_P.
  • Ranges are arbitrary, selected by Randy Swaty. Pay special attention to negatives, and the 0-20 category. It may be that we need to adjust ranges.
  • All the charts are available for download. Click this link to download a .zip file. The file will be automatically downloaded, probably to your “Downloads” folder.
  • BPs from Burn Unit 22 and BP 40-10 are missing from charts presumably due to there not being counts for the matching years.

sessionInfo()
R version 3.6.2 (2019-12-12)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19041)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252 
[2] LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] slickR_0.5.0         ggforce_0.3.3        plotly_4.9.3        
 [4] crosstalk_1.1.1.9000 DT_0.18              ggtext_0.1.1        
 [7] ggsci_2.9            forcats_0.5.1        stringr_1.4.0       
[10] dplyr_1.0.5          purrr_0.3.4          readr_1.4.0         
[13] tidyr_1.1.3          tibble_3.1.1         ggplot2_3.3.3.9000  
[16] tidyverse_1.3.1     

loaded via a namespace (and not attached):
 [1] nlme_3.1-152      fs_1.5.0          lubridate_1.7.10  httr_1.4.2       
 [5] rprojroot_2.0.2   tools_3.6.2       backports_1.2.1   bslib_0.2.4      
 [9] utf8_1.2.1        R6_2.5.0          mgcv_1.8-35       DBI_1.1.1        
[13] lazyeval_0.2.2    colorspace_2.0-0  withr_2.4.2       tidyselect_1.1.0 
[17] compiler_3.6.2    git2r_0.28.0      cli_2.5.0         rvest_1.0.0      
[21] pacman_0.5.1      xml2_1.3.2        labeling_0.4.2    sass_0.3.1       
[25] scales_1.1.1      digest_0.6.27     rmarkdown_2.7.4   base64enc_0.1-3  
[29] pkgconfig_2.0.3   htmltools_0.5.1.1 fastmap_1.1.0     dbplyr_2.1.1     
[33] highr_0.9         htmlwidgets_1.5.3 rlang_0.4.10      readxl_1.3.1     
[37] rstudioapi_0.13   shiny_1.6.0       jquerylib_0.1.3   farver_2.1.0     
[41] generics_0.1.0    jsonlite_1.7.2    magrittr_2.0.1    Matrix_1.3-2     
[45] Rcpp_1.0.6        munsell_0.5.0     fansi_0.4.2       lifecycle_1.0.0  
[49] stringi_1.5.3     whisker_0.4       yaml_2.2.1        MASS_7.3-53.1    
[53] grid_3.6.2        promises_1.2.0.1  crayon_1.4.1      lattice_0.20-41  
[57] splines_3.6.2     haven_2.4.1       gridtext_0.1.4    hms_1.0.0        
[61] knitr_1.33        pillar_1.6.0      reprex_2.0.0      glue_1.4.2       
[65] evaluate_0.14     data.table_1.14.0 modelr_0.1.8      vctrs_0.3.7      
[69] tweenr_1.0.2      httpuv_1.6.0      cellranger_1.1.0  gtable_0.3.0     
[73] polyclip_1.10-0   assertthat_0.2.1  xfun_0.22         mime_0.10        
[77] xtable_1.8-4      broom_0.7.6       later_1.2.0       viridisLite_0.4.0
[81] workflowr_1.6.2   ellipsis_0.3.1